WO2022227536A1

WO2022227536A1 - Robot arm control method and apparatus, and robot arm and readable storage medium

Info

Publication number: WO2022227536A1
Application number: PCT/CN2021/133002
Authority: WO
Inventors: 黄荔群; 任晓雨; 赵明国; 熊友军
Original assignee: 深圳市优必选科技股份有限公司
Priority date: 2021-04-26
Filing date: 2021-11-25
Publication date: 2022-11-03
Also published as: CN113510698B; CN113510698A

Abstract

A robot arm control method. The method comprises: by using a sensor at the tail end of a robot arm (200), acquiring, in a tail end coordinate system, n pieces of gravity matrix data of a manipulator at the tail end of the robot arm (200) when same is at n different attitudes, wherein n ≥ 3; determining, by using a preset rotation transformation matrix determination method, n rotation transformation matrices of the robot arm (200) from a base coordinate system to the tail end coordinate system when the robot arm (200) is at the n different attitudes; and calculating the centroid coordinates and mass of the manipulator merely by acquiring the n pieces of corresponding gravity matrix data of the robot arm (200) when same is at the n different attitudes, and the n rotation transformation matrices of same. By means of the method, a power-on error of a force sensor is fully taken into consideration, and not only is the amount of calculation small, but online data processing can also be realized; and the centroid coordinates and mass of a manipulator are determined, without needing to modify model parameters after offline solving, thereby effectively increasing the speed of determining relevant parameters of a manipulator. Further provided are a robot arm control apparatus (10), a robot arm (200) and a readable storage medium.

Description

A manipulator control method, device, manipulator and readable storage medium

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the priority of the Chinese Patent Application No. 2021104548636 and titled "A Manipulator Control Method, Device, Manipulator and Readable Storage Medium" filed with the China Patent Office on April 26, 2021, all of which The contents are incorporated herein by reference.

technical field

The present application relates to the technical field of robotic arm applications, and in particular, to a robotic arm control method, a device, a robotic arm, and a readable storage medium.

Background technique

With the promotion and popularization of robotic arms in the field of service robots, robotic arms are usually replaced by robotic arms to perform different tasks, and for different tasks, different manipulators are installed at the end of the robotic arm to grab or grip the load For example, a sucker-type manipulator can be used when grabbing boxes, a multi-finger gripper can be used when grabbing irregular items, and a corresponding pen clip can be installed when writing. Manipulators with different mass properties will affect the position and force control of the robotic arm.

In the prior art, the relevant mass and centroid parameters can be obtained through the CAD model of the manipulator. However, due to differences in processing, assembly, electrical components, etc. from the theory, the actual quality parameters are different from the CAD model, and many manipulators installed at the end of the manipulator cannot use the CAD model to obtain their theoretical model parameters. As a result, the control end of the manipulator cannot accurately obtain the mass and center of mass of the manipulator, so that the control end of the manipulator cannot perform precise position movement and force control of the manipulator.

Application content

In view of the above problems, the present application proposes a method, device, robot arm and readable storage medium for controlling a robotic arm.

The present application proposes a method for controlling a robotic arm, the method comprising:

The n gravity matrix data of the manipulator installed at the end of the manipulator is obtained by using the sensor installed at the end of the manipulator, and the n gravity matrix data is when the manipulator is in n different poses. n gravity matrix data in the end coordinate system, n≥3;

determining n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses;

Use the n gravity matrix data and the n rotation transformation matrices to calculate the center of mass coordinates and mass of the operator;

The center of mass coordinates and the mass are fed back to the control end of the robotic arm, so that the control end of the robotic arm controls the robotic arm according to the center of mass coordinates and the mass.

In the robotic arm control method described in the present application, the acquisition of n gravity matrix data of the manipulator at the end of the robotic arm by using a sensor installed at the end of the robotic arm includes:

Control the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation;

When the manipulator maintains the jth pose, the sensor installed at the end of the manipulator is used to obtain the jth gravity matrix data of the manipulator in the coordinate system of the end, where j≤n.

In the manipulator control method described in the present application, the preset rotation transformation matrix determination method is used to determine the number of n points from the base coordinate system of the manipulator to the end coordinate system when the manipulator is in n different poses Rotation transformation matrix, including:

When the robotic arm maintains the jth pose, j≤n:

Obtain the joint angle of each link of the robotic arm;

Determine the adjacent transformation matrix between the coordinate systems of each adjacent connecting rod by using the joint angle of each connecting rod and the preset twisting degree of each connecting rod;

Use each adjacent transformation matrix to determine the jth rotation transformation matrix corresponding to the jth pose.

The manipulator control method described in this application uses the following formulas to determine the center of mass coordinates and mass of the manipulator:

j=1, 2 or 3, m represents the mass of the manipulator, rc represents the center of mass coordinates of the manipulator, fFTbias represents the static error of the force collected by the sensor installed at the end of the manipulator, τFTbias represents the The static error of the torque collected by the sensor at the end of the robot arm, Yj represents the parameter matrix corresponding to the jth pose,

represents the transpose matrix corresponding to the jth rotation transformation matrix, g represents the gravitational acceleration vector,

express request

the antisymmetric matrix of Gravity matrix data, fFTj represents the force vector of the gravity matrix data corresponding to the jth pose, and τFTi represents the moment vector of the gravity matrix data corresponding to the jth pose.

In the method for controlling the robotic arm described in the present application, the control of the robotic arm to arbitrarily transform n times within the motion range, and to maintain the current pose for a preset time after each transformation, includes:

Controlling the end of the robotic arm to move to preset n end positions in sequence, and staying at each end position for a preset time, and the preset n end positions are within the motion range;

Or, use a random function to randomly select n end positions within the motion range, control the end of the robotic arm to move to the n end positions in sequence, and stay at each end position for a preset time;

Or, under the condition that the end position of the robotic arm is kept unchanged, each link of the robotic arm is controlled to be arbitrarily transformed n times within the motion range, and the current pose is maintained for a preset time after each transformation.

In the robotic arm control method described in the present application, the value range of the preset time is 1s to 2s.

The robotic arm control method described in the present application further includes: feeding back the static error of the sensor installed at the end of the robotic arm to the control end of the robotic arm.

The present application proposes a robotic arm control device, the device comprising:

The acquisition module is used to obtain n pieces of gravity matrix data of the manipulator installed at the end of the robot arm by using the sensor installed at the end of the robot arm, where the n pieces of gravity matrix data are when the robot arm is in n different poses n gravity matrix data of the operator in the end coordinate system, n≥3;

A determination module, configured to use a preset rotation transformation matrix determination method to determine n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses;

a calculation module for calculating the coordinates of the center of mass and the mass of the operator by using the n gravity matrix data and the n rotation transformation matrices;

The control module is configured to feed back the coordinates of the center of mass and the mass to the control end of the manipulator, so that the control end of the manipulator controls the manipulator according to the coordinates of the center of mass and the mass.

The present application proposes a robotic arm, including a memory and a processor, wherein the memory stores a computer program, and the computer program executes the robotic arm control method described in the present application when the computer program runs on the processor.

The present application provides a readable storage medium, which stores a computer program, and when the computer program runs on a processor, executes the robotic arm control method described in the present application.

The technical solution of the present application uses the sensor at the end of the manipulator to obtain n gravity matrix data of the manipulator at the end of the manipulator in the end coordinate system when the manipulator is in n different poses, n≥3; determine the When the manipulator is in n different poses, the n rotation transformation matrices from the base coordinate system of the manipulator to the end coordinate system; it is only necessary to use the n gravity matrix data corresponding to the manipulator in n different poses and With n rotation transformation matrices, the center of mass coordinates and mass of the operator can be calculated. The technical solution for calculating the coordinates of the center of mass and the mass of the manipulator disclosed in the present application not only requires a small amount of calculation, but also can realize online data processing to determine the coordinates and mass of the center of mass of the manipulator, without the need to solve the offline solution and then modify the model parameters, thereby effectively The speed of determining the relevant parameters of the manipulator is improved; and, the control method of the manipulator disclosed in the present application also feeds back the coordinates of the center of mass and the mass to the control end of the manipulator, so that the control end of the manipulator can be The coordinates of the center of mass and the quality control the robotic arm, so that the control end of the robotic arm can perform accurate force control on the robotic arm, thereby controlling the robotic arm to move precisely.

Description of drawings

In order to illustrate the technical solutions of the present application more clearly, the following briefly introduces the accompanying drawings used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be It is regarded as a limitation on the protection scope of this application. In the various figures, similar components are numbered similarly.

FIG. 1 shows a schematic flowchart of a method for controlling a robotic arm proposed by an embodiment of the present application;

2 shows a schematic flowchart of a method for determining n gravity matrix data proposed by an embodiment of the present application;

3 shows a schematic flowchart of a method for determining a rotation transformation matrix proposed by an embodiment of the present application;

FIG. 4 shows a schematic diagram of related parameters of a robotic arm proposed by an embodiment of the present application;

FIG. 5 shows a schematic flowchart of another method for controlling a robotic arm proposed by an embodiment of the present application;

FIG. 6 shows a schematic structural diagram of a robotic arm control device proposed in an embodiment of the present application;

FIG. 7 shows a schematic structural diagram of a robotic arm proposed in an embodiment of the present application.

Description of main component symbols:

10-manipulator control device; 11-acquisition module; 12-determination module; 13-calculation module; 14-control module; 200-manipulator; 210-memory; 220-processor.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

Hereinafter, the terms "comprising", "having" and their cognates, which may be used in various embodiments of the present application, are only intended to denote particular features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the presence of or adding one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing or the possibility of a combination of the foregoing.

Furthermore, the terms "first", "second", "third", etc. are only used to differentiate the description and should not be construed as indicating or implying relative importance.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized or overly formal meaning, unless explicitly defined in the various embodiments of the present application.

Considering that when the manipulator moves, the position and posture of the manipulator installed at the end of the manipulator will change. Without considering the interference of external forces on the manipulator, the manipulator at the end is only affected by gravity, due to the gravitational field. The direction of the manipulator does not change, so the gravity is unchanged in the base coordinate system of the manipulator. However, the value of the manipulator's gravity relative to the coordinate system of the end of the manipulator will change with the movement of the manipulator. Therefore, the quality attributes of the manipulator can be automatically identified according to the above characteristics.

Further, the technical solution of the present application can be used on a manipulator of any configuration. After a new manipulator is installed at the end of the manipulator, the manipulator parameter automatic identification method disclosed in the present application is used to power on the manipulator and initialize the manipulator. Only need to collect the relevant information corresponding to three random poses to calculate the center of mass coordinates and mass of the manipulator. Not only the calculation amount is small, but also online data processing can be realized, without the need to solve offline and then modify the model parameters, and update the relevant parameter information of the operator in real time. In addition, the automatic identification method of manipulator parameters disclosed in the present application fully considers the power-on error of the force sensor when calculating the center of mass coordinates and mass of the manipulator, so that the center of mass coordinates and mass of the manipulator determined by calculation are closer to the real values.

Example 1

An embodiment of the present application proposes a method for controlling a robotic arm. As shown in FIG. 1 , the method for controlling a robotic arm includes the following steps:

S100: Acquire n pieces of gravity matrix data of the manipulator installed at the end of the robotic arm by using a sensor installed at the end of the robotic arm, where the n pieces of gravity matrix data are the operations when the robotic arm is in n different poses n gravity matrix data of the device in the end coordinate system, n≥3.

Since the contact between the manipulator and the working surface is often an unknown complex surface, when determining the manipulator gravity of the manipulator at the end of the manipulator in the end coordinate system, it is necessary to use a six-dimensional force sensor to obtain n different positions of the manipulator. The n gravity matrix data of the manipulator at the end of the manipulator in the end coordinate system during the pose. The 6-Dimension Force Torque Sensor is a force sensor that can measure multi-dimensional force/torque at the same time, and convert the multi-dimensional force/torque signal into an electrical signal, which can be used to monitor forces and torques with changing directions and magnitudes. , you can measure acceleration or inertial force and detect the magnitude and point of contact force. It can be understood that the six-dimensional force sensor can measure the force and torque in the three directions of space X, Y, and Z.

Further, referring to Fig. 2, the method for determining n gravity matrix data includes the following steps:

S110: Control the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation.

It can be understood that the methods for controlling the robotic arm to arbitrarily transform n times within the motion range include the following three methods:

First, n end positions can be preset within the motion range of the manipulator, and then the end of the manipulator is controlled to move to the preset n end positions in sequence, and stay at each end position for a preset time.

Second, a random function can be used to randomly select n end positions within the motion range of the manipulator, and then control the end of the manipulator to move to n randomly selected end positions in sequence, and stay at each end position for a preset time.

Thirdly, while keeping the end position of the robotic arm unchanged, each link of the robotic arm can be controlled to be arbitrarily transformed n times within the range of motion, and after each transformation, the current pose.

Optionally, the value range of the preset time for maintaining the current pose can be 1s to 2s, and the principle of setting the preset time is: it should be ensured that the sensor installed at the end of the robot arm can obtain a stable sensor within the preset time. Gravity Matrix Data. Preferably, the preset time can be 1s, which can ensure that the sensor installed at the end of the robotic arm can obtain stable gravity matrix data within the preset time, and can avoid the entire automatic parameter identification process taking a long time.

S120: When the manipulator maintains the jth pose, use the sensor installed at the end of the manipulator to acquire the jth gravity matrix data of the manipulator in the coordinate system of the end, where j≤n.

When the robotic arm maintains each pose, the six-dimensional force sensor installed at the end of the robotic arm is used to obtain the corresponding gravity matrix data of the manipulator in the end coordinate system.

It is understandable that without considering the interference of external forces on the manipulator, the manipulator at the end is only affected by gravity. Since the direction of the gravity field will not change, the magnitude of gravity is in the base coordinate system of the robotic arm. However, the value of gravity relative to the coordinate system of the end of the manipulator will change with the movement of the manipulator. Therefore, the mass properties of the manipulator can be identified by using the obtained multiple gravity matrix data.

S200: Determine n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses.

A rotation transformation matrix determination method can be used to determine n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses, and the rotation transformation matrix determination method includes the standard DH ( At least one of Denavit-Hartenberg) method, modified DH method and S-U (Sheth and Uicker) method. Exemplarily, the DH method can be used to model the robot, and when the manipulator is in different poses, the link joint angles of each link of the manipulator in different poses are obtained, and then, through each link of the manipulator. The joint angle of the link, the preset twist of each link, and the offset of each link can determine the rotation transformation matrix. Among them, the twist degree of each link and the offset of each link are related to the configuration of the manipulator. When the configuration of the manipulator is constant, determine the twist degree of each link and the offset of each link corresponding to the configuration of the manipulator, and set the The twist of each link and the offset of each link are used as preset values.

Exemplarily, referring to FIG. 3, the n rotation transformation matrices are determined using the following steps:

S210: Control the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation.

It can be understood that the method for controlling the robotic arm to arbitrarily transform n times within the range of motion includes: setting n end positions within the range of motion of the robotic arm in advance, and then controlling the end of the robotic arm to move to a preset position in sequence. n end positions, and stay at each end position for a preset time; a random function can be used to randomly select n end positions within the motion range of the manipulator, and then control the end of the manipulator to move to n randomly selected end position, and stay at each end position for a preset time; it is also possible to control each link of the robotic arm to arbitrarily change n times within the range of motion while keeping the end position of the robotic arm unchanged, and The current pose is maintained for a preset time after each transformation.

Optionally, the value range of the preset time for maintaining the current pose may be 1s to 2s, and the principle of setting the preset time is: it should be ensured that the preset rotation transformation matrix determination method can be used to determine the corresponding value within the preset time. The rotation transformation matrix of . Preferably, the preset time may be 1 s, that is, it can be ensured that the preset rotation transformation matrix determination method can determine the corresponding rotation transformation matrix within the preset time, and the entire automatic parameter identification process can be prevented from taking a long time.

Further, when the robotic arm maintains the jth pose, j≤n, the following steps S220 to S240 are performed until the nth rotation transformation matrix is determined when j=n.

S220: Obtain the joint angles of each link of the robotic arm.

The angular displacement sensor or position encoder at the corresponding position of each joint of the manipulator can be used to collect the link angle of the corresponding joint.

S230: Determine the adjacent transformation matrix between the coordinate systems of each adjacent link by using the joint angle of each link and the preset twist degree of each link.

S240: Use each adjacent transformation matrix to determine the jth rotation transformation matrix corresponding to the jth pose.

It can be understood that the DH method is used to model the robot. When the manipulator is in different poses, the link angle of the i-th link of the manipulator can be obtained through the position encoder or angular displacement sensor of each joint of the manipulator. q ⁱ , using the link joint angle q _i of the ith link, the preset link twist α _i of the ith link, and the link offset d _i of the ith link, the adjacent two links can be calculated. Homogeneous transformation matrix of a coordinate system

for:

Exemplarily, as shown in Figure 4, a robotic arm includes multiple links and multiple link joints, "link i-1" represents the i-1th link, and "link i" represents the ith link. Rod, "Joint 1" represents the 1st link joint, "Joint i-1" represents the i-1th link joint, "Joint i" represents the ith link joint, and "Joint i+1" represents the ith link joint i+1 link joints, qi represents the link angle of the _{ith link, α i} _represents the preset link twist of the ith link, d _i represents the link of the ith link Bias.

Further, the homogeneous transformation matrix

The first three rows of can represent the adjacent transformation matrix

Among them, the adjacent transformation matrix

The coordinate system corresponding to the i link between the coordinate system corresponding to the i-th link and the coordinate system corresponding to the i-1-th link can be represented.

After determining the adjacent transformation matrix between every two adjacent links, according to

The rotation transformation matrix Rj from the base coordinate system to the end coordinate system of the manipulator corresponding to the jth pose can be determined. Among them, L is the total number of connecting rods.

S300: Calculate the coordinates of the center of mass and the mass of the operator by using the n pieces of gravity matrix data and the n pieces of rotation transformation matrices.

The center of mass coordinates and mass of the operator may be calculated using the n gravity matrix data and the n rotation transformation matrices.

S400: Feed back the coordinates of the centroid and the mass to the control end of the robotic arm, so that the control end of the robotic arm controls the robotic arm according to the coordinates of the centroid and the mass.

Feedback the coordinates of the center of mass and the mass to the control end of the robotic arm, so that the control end of the robotic arm controls the robotic arm according to the coordinates of the center of mass and the mass, so that the control end of the robotic arm can Accurate force control of the robotic arm, so as to control the precise position movement of the robotic arm.

It can be understood that the above steps S100 and S200 can be executed simultaneously or sequentially. When executed sequentially, there is no sequence between steps S100 and S200. However, when executed sequentially, the jth rotation transformation matrix and the jth rotation transformation matrix should be guaranteed. The j gravity matrix data corresponds to the jth pose that is the same. Preferably, step S100 and step S200 are performed at the same time, and at the jth pose, the jth rotation transformation matrix and the jth gravity matrix data are determined simultaneously, and the simultaneous execution of steps S100 and S200 can speed up the center of mass coordinates and mass of the manipulator recognition speed.

The technical solution of this embodiment uses the sensor at the end of the manipulator to obtain n gravity matrix data of the manipulator at the end of the manipulator in the end coordinate system when the manipulator is in n different poses, n≥3; The set rotation transformation matrix determination method determines n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses; it is only necessary to obtain the n different positions of the robotic arm. According to the n gravity matrix data and n rotation transformation matrices corresponding to the posture, the center of mass coordinates and mass of the manipulator can be calculated. The technical solution for calculating the coordinates of the center of mass and the mass of the manipulator disclosed in the present application not only requires a small amount of calculation, but also can realize online data processing to determine the coordinates and mass of the center of mass of the manipulator, without the need to solve the offline solution and then modify the model parameters, thereby effectively The speed of determining the relevant parameters of the manipulator is improved; and the technical solution of feeding back the coordinates of the center of mass and the mass to the control end of the manipulator disclosed in the present application enables the control end of the manipulator to The coordinates and the quality control the robotic arm, so that the control end of the robotic arm can perform accurate force control on the robotic arm, so as to control the robotic arm to perform precise position movement.

Example 2

Further, the following formulas are used to determine the coordinates of the center of mass and the mass of the manipulator:

in,

j=1, 2, or 3, m represents the mass of the manipulator, rc represents the center of mass coordinates of the manipulator, fFTbias represents the static error of the force collected by the sensor at the end of the manipulator, τFTbias represents the force of the manipulator at the end of the manipulator The static error of the sensor acquisition moment, Yj represents the parameter matrix corresponding to the jth pose,

express request

It should be understood that, every time the six-dimensional force sensor is powered on and used, the collected values obtained by the six-dimensional force sensor have static errors, and the static errors are different each time. Generally, the six-dimensional force sensor needs to stand for a period of time before use, and then the static error of the six-dimensional force sensor is measured and then used to measure the force. However, the six-dimensional force sensor and the manipulator at the end need to be removed every time, and the static error is measured before use, which is very time-consuming and inconvenient. If the six-dimensional force and the manipulator at the end are not removed for measurement, the static error will be affected by the manipulator at the end, resulting in a large error in the six-dimensional force measurement result. Therefore, in the formula for determining the center of mass coordinates and mass of the manipulator disclosed in this application, considering the influence of the static error of the six-dimensional force sensor after each power-on, fFTbias is used to represent the force obtained by the sensor at the end of the robotic arm. The static error, τFTbias, represents the static error of the torque acquired by the sensor at the end of the robot arm.

Further, it is assumed that Σ _base is the base coordinate system of the manipulator, Σ _FT is the end coordinate system of the six-dimensional force sensor installed at the end of the manipulator, and Σ _load is the coordinate system located at the center of mass of the end manipulator. At any time, the magnitude of the gravitational force on the center of mass of the end manipulator remains unchanged in the base coordinate system, which can be expressed as

where m is the mass of the manipulator at the end, and ^g∈R3 is the acceleration of gravity.

Further, the gravity of the manipulator collected by the six-dimensional force sensor installed at the end of the manipulator will be affected by the motion of the manipulator, and the collected value also includes the static error after the six-dimensional force sensor is powered on. Therefore, the gravity matrix data collected by the six-dimensional force sensor can be obtained as

and,

is the value of the gravity received by the operator at the end in the end coordinate system where the six-dimensional force sensor is located,

is the static error of the six-dimensional force sensor. because,

and

It is only the representation of the gravity of the center of mass of the manipulator at the end in different coordinate systems. Therefore, the conversion relationship between the two can be obtained according to the configuration and coordinate conversion of the manipulator. r _c =[r _cx ,r _cy , _r _cz ] is the center of mass coordinates of the operator at the end, S is the antisymmetric matrix for calculating the rc vector,

is the rotation transformation matrix from the base coordinate system to the six-dimensional force sensor.

That is, the adjacent transformation matrices from the base of the manipulator to the six-dimensional force sensor are multiplied in turn.

Further, the mass, center of mass coordinates, and static error of the sensor that need to be identified are proposed, and the following expression can be obtained:

Among them, the parameters that need to be identified

There are 10 in total, and

It is a 6*10 matrix, and only the data of one point cannot obtain the required parameters. Therefore, the Y matrix is judged to find out the minimum number of robot information that needs to be collected. Assuming that the information of n points is required, the six-dimensional force information of n points and the identification matrix are combined as follows:

To solve the problem, the row rank of the Y matrix should be greater than the number of identification parameters, that is, rank(Y)≥10. It can be obtained through analysis that when n=1, rank(Y)=5, and when m=2 rank(Y)=9, when n≥3, rank(Y)=10, therefore, for a manipulator with any number of joints, at least three different manipulator poses are needed to solve the manipulator at the end. parameters and the static error of the six-dimensional force sensor, and do not need to be solved step by step, as long as the three gravity matrix data and three rotation transformation matrix data corresponding to the three poses are collected, the center of mass coordinates rc and mass of the operator at the end can be solved m.

Example 3

Further, referring to FIG. 5 , the method for controlling the robotic arm further includes the following steps:

S500: Feedback the static error of the sensor installed at the end of the robotic arm to the control end of the robotic arm.

Feedback the static error of the sensor installed at the end of the manipulator to the control end of the manipulator, so that the control end can perform the gravitational direction and the static error according to the coordinates of the center of mass of the manipulator, the mass and the static error of the sensor at the end of the manipulator. Compensate, and then issue accurate control commands, improve control accuracy, and improve the dynamic and steady-state performance of the robotic arm.

Example 4

An embodiment of the present application, as shown in FIG. 6 , proposes a robotic arm control device 10 including an acquisition module 11 , a determination module 12 , a calculation module 13 and a control module 14 .

The acquisition module 11 is used to obtain n pieces of gravity matrix data of the manipulator at the end of the robotic arm by using the sensor at the end of the robotic arm, where the n pieces of gravity matrix data are the operations when the robotic arm is in n different poses n gravity matrix data of the robot in the end coordinate system, n≥3; the determination module 12 is used to determine the base of the robot arm when the robot arm is in n different poses by using a preset rotation transformation matrix determination method n rotation transformation matrices from the coordinate system to the end coordinate system; the calculation module 13 is used to calculate the center of mass coordinates and mass of the operator by using the n gravity matrix data and the n rotation transformation matrices; the control module 14, used to feed back the coordinates of the center of mass and the mass to the control end of the robotic arm, so that the control end of the robotic arm controls the robotic arm according to the coordinates of the center of mass and the quality; also used for The static error of the sensor installed at the end of the robotic arm is fed back to the control end of the robotic arm.

Further, using the sensor at the end of the manipulator to obtain n pieces of gravity matrix data of the manipulator at the end of the manipulator in the end coordinate system when the manipulator is in n different poses includes: controlling the manipulator. Arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation; when the robotic arm maintains the jth pose, use the sensor at the end of the robotic arm to obtain the manipulator The jth gravity matrix data in the end coordinate system, j≤n.

Further, determining the n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses by using a preset rotation transformation matrix determination method includes: controlling The robotic arm arbitrarily transforms n times within the motion range, and maintains the current pose for a preset time after each transformation; when the robotic arm maintains the jth pose, j≤n:

The joint angle of each link of the mechanical arm is obtained by using the encoder of each joint position of the mechanical arm; the phase between the coordinate systems of each adjacent link is determined by using the joint angle of each link and the preset twist of each link. Adjacent transformation matrix; use each adjacent transformation matrix to determine the jth rotation transformation matrix corresponding to the jth pose.

j=1, 2 or 3, m represents the mass of the manipulator, rc represents the center of mass coordinates of the manipulator, fFTbias represents the static error of the force acquired by the sensor at the end of the robot arm, τFTbias represents the end of the robot arm The static error of the moment obtained by the sensor, Yj represents the parameter matrix corresponding to the jth pose,

express request

the antisymmetric matrix of Gravity matrix data, fFTj represents the force vector corresponding to the gravity matrix data corresponding to the jth pose, and τFTi represents the torque vector corresponding to the gravity matrix data corresponding to the jth pose.

Further, the control of the robotic arm to arbitrarily transform n times within the range of motion, and to maintain the current pose for a preset time after each transformation, includes:

Control the end of the robotic arm to move to preset n end positions in sequence, and stay at each end position for a preset time, and the preset n end positions are within the motion range; or, use a random function Randomly select n end positions within the motion range, control the end of the robotic arm to move to n end positions in sequence, and stay at each end position for a preset time; or, keep the end position of the robotic arm Under the condition that it remains unchanged, each link that controls the mechanical arm is arbitrarily transformed n times within the motion range, and the current pose is maintained for a preset time after each transformation.

Further, the value range of the preset time is 1s˜2s.

The robotic arm control device 10 disclosed in this embodiment is used in conjunction with the acquisition module 11 , the determination module 12 , the calculation module 13 and the control module 14 to execute the robotic arm control method described in the foregoing embodiments. The implementation and beneficial effects are also applicable to this embodiment, and will not be repeated here.

Some embodiments of the present application, as shown in FIG. 7 , provide a robotic arm 200 including a memory 210 and a processor 220 , the memory 210 stores a computer program, and the computer program runs on the processor 220 Execute the robotic arm control method described in this application.

The present application also provides a readable storage medium, which stores a computer program, and when the computer program runs on the processor, executes the robotic arm control method described in the present application.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may also be implemented in other manners. The apparatus embodiments described above are only schematic. For example, the flowcharts and structural diagrams in the accompanying drawings show the possible implementation architectures and functions of the apparatuses, methods and computer program products according to various embodiments of the present application. and operation. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more functions for implementing the specified logical function(s) executable instructions. It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams and/or flow diagrams, and combinations of blocks in the block diagrams and/or flow diagrams, can be implemented using dedicated hardware-based systems that perform the specified functions or actions. be implemented, or may be implemented in a combination of special purpose hardware and computer instructions.

In addition, each functional module or unit in each embodiment of the present application may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

If the functions are implemented in the form of software function modules and sold or used as independent products, they may be stored in a readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this. should be covered within the scope of protection of this application.

Claims

A method for controlling a robotic arm, wherein the method comprises:

The n gravity matrix data of the manipulator installed at the end of the manipulator is obtained by using the sensor installed at the end of the manipulator, and the n gravity matrix data is when the manipulator is in n different poses. n gravity matrix data in the end coordinate system, n≥3;

determining n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses;

Use the n gravity matrix data and the n rotation transformation matrices to calculate the center of mass coordinates and mass of the operator;

The center of mass coordinates and the mass are fed back to the control end of the robotic arm, so that the control end of the robotic arm controls the robotic arm according to the center of mass coordinates and the mass.
The method for controlling a robotic arm according to claim 1, wherein the acquisition of n pieces of gravity matrix data of the manipulator mounted at the end of the robotic arm by using a sensor mounted at the end of the robotic arm comprises:

Control the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation;

When the manipulator maintains the jth pose, the sensor installed at the end of the manipulator is used to obtain the jth gravity matrix data of the manipulator in the coordinate system of the end, where j≤n.
The method for controlling a robotic arm according to claim 1, wherein the base coordinate system of the robotic arm is determined by using a preset rotation transformation matrix determination method when the robotic arm is in n different poses to the n rotation transformation matrices of the end coordinate system, including:

Control the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation;

When the robotic arm maintains the jth pose, j≤n:

Obtain the joint angle of each link of the robotic arm;

Determine the adjacent transformation matrix between the coordinate systems of each adjacent connecting rod by using the joint angle of each connecting rod and the preset twisting degree of each connecting rod;

Use each adjacent transformation matrix to determine the jth rotation transformation matrix corresponding to the jth pose.
The manipulator control method according to claim 1, wherein the following formulas are used to determine the coordinates of the center of mass and the mass of the manipulator:

m represents the mass of the manipulator, rc represents the coordinates of the center of mass of the manipulator, fFTbias represents the static error of the force collected by the sensor installed at the end of the robot arm, and τFTbias represents the torque collected by the sensor installed at the end of the robot arm. Static error, Yj represents the parameter matrix corresponding to the jth pose,
represents the transpose matrix corresponding to the jth rotation transformation matrix, g represents the gravitational acceleration vector,
express request
the antisymmetric matrix of Gravity matrix data, fFTj represents the force vector of the gravity matrix data corresponding to the jth pose, and τFTi represents the moment vector of the gravity matrix data corresponding to the jth pose.
The method for controlling a robotic arm according to claim 2 or 3, wherein the controlling the robotic arm to arbitrarily transform n times within the motion range, and maintain the current pose for a preset time after each transformation, comprising: :

Controlling the end of the robotic arm to move to preset n end positions in sequence, and staying at each end position for a preset time, and the preset n end positions are within the motion range;

Or, use a random function to randomly select n end positions within the motion range, control the end of the robotic arm to move to the n end positions in sequence, and stay at each end position for a preset time;

Or, under the condition that the end position of the robotic arm is kept unchanged, each link of the robotic arm is controlled to be arbitrarily transformed n times within the motion range, and the current pose is maintained for a preset time after each transformation.
The method for controlling a robotic arm according to claim 2 or 3, wherein the preset time ranges from 1s to 2s.
The method for controlling a robotic arm according to claim 4, further comprising: feeding back the static error of the sensor installed at the end of the robotic arm to the control end of the robotic arm.
A mechanical arm control device, characterized in that the device comprises:

The acquisition module is used to obtain n pieces of gravity matrix data of the manipulator installed at the end of the robot arm by using the sensor installed at the end of the robot arm, where the n pieces of gravity matrix data are when the robot arm is in n different poses n gravity matrix data of the operator in the end coordinate system, n≥3;

A determination module, configured to use a preset rotation transformation matrix determination method to determine n rotation transformation matrices from the base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses;

a calculation module for calculating the coordinates of the center of mass and the mass of the operator by using the n gravity matrix data and the n rotation transformation matrices;

The control module is configured to feed back the coordinates of the center of mass and the mass to the control end of the manipulator, so that the control end of the manipulator controls the manipulator according to the coordinates of the center of mass and the mass.
A robotic arm, characterized in that it comprises a memory and a processor, the memory stores a computer program, and the computer program executes the robotic arm control described in any one of claims 1 to 7 when the computer program runs on the processor method.
A readable storage medium, characterized in that it stores a computer program, and the computer program executes the robotic arm control method according to any one of claims 1 to 7 when the computer program runs on a processor.